Researchers from MIT and GM propose a tool for better estimating secondary mass savings potential; maximizing vehicle mass savings for greater fuel economy
|More accurately estimating SMS can maximize mass savings, thereby increasing fuel economy. Credit: ACS, Alonso et al. Click to enlarge.|
Researchers from MIT and GM have developed a tool for estimating secondary mass savings potential early in the vehicle design process. Using the tool early in the process—before subsystems become locked in—maximizes mass savings, they report in a paper published in the ACS journal Environmental Science & Technology.
Secondary mass savings are mass reductions that may be achieved in supporting (load-bearing) vehicle parts when the gross vehicle mass (GVM) is reduced. Mass decompounding is the process by which it is possible to identify further reductions when secondary mass savings result in further reduction of GVM. Maximizing secondary mass savings (SMS) is a key tool for maximizing vehicle fuel economy, they note, but can be difficult to achieve given the current design process.
Various engineering and design approaches can be used to reduce mass, including materials substitution, novel processing techniques, and design optimization. A number of authors have noted that all of these mass saving approaches are challenging to implement because it is difficult to estimate their impact on costs and on load path management.
An additional challenge emerges from the nature of the vehicle development process, which is time-constrained and in which subsystems are designed concurrently. As such, to maximize mass savings it is necessary to have sound estimates of the impact of any mass solution, and those estimates must be available early, before key design details are locked in. This paper will focus solely on one aspect of addressing this information challenge for mass reduction engineering: estimating secondary mass saving (SMS) for proposed mass solutions. With a better understanding of SMS potential, vehicle designers should be better able to set early mass targets and analysts should be able to develop better estimates of the life-cycle cost, fuel use, and environmental impact of mass changes.—Alonso et al.
SMS essentially reflects that the size (and mass) of some components is at least partially determined by the need to bear the mass of other components—i.e., if vehicle mass decreases, the mass of some components can also decrease. SMS, the authors note, can increase the attractiveness of any proposed mass reduction by increasing the realized mass change associated with any significant primary reduction.
The implications of this are simple: if vehicle manufacturers underestimate SMS, they are more likely to think that any given mass reduction solution has too little impact, is too costly, or both.
Implementing (and therefore estimating) SMS is challenging because of fundamental limitations related to the vehicle development process, use of carryover parts, and component sharing. The vehicle development process lasts 50−60 months before vehicle launch, and to accommodate the complexity and cost of change, it involves locking in certain vehicle subsystem designs as the process progresses. Once a subsystem is locked, its components are no longer available to realize SMS.—Alonso et al.
In their paper, Alonso et al. work to improve empirical estimation of SMS potential by:
- providing a formal statement of the analytical method;
- developing the methods for quantifying uncertainty in the estimation of SMS potential;
- characterizing the inherent upper-bound bias of this method; and
- quantifying the importance of expert classification of data at the component level for managing the impact of mass-independent effects on the analysis.
The team estimated the potential for SMS in current passenger vehicles with an empirical model using engineering analysis of vehicle components to determine mass-dependency. They grouped the identified mass-dependent components into subsystems, and performed linear regression on subsystem mass as a function of GVM.
A Monte Carlo simulation determined the mean and 5th and 95th percentiles for the SMS potential per kilogram of primary mass saved.
The model projects that the mean theoretical secondary mass savings potential is 0.95 kg for every 1 kg of primary mass saved, with the 5th percentile at 0.77 kg/kg when all components are available for redesign.
Using the model to explore an alternative scenario where realistic manufacturing and design limitations were implemented, they found four key subsystems (of 13 total) were locked-in. This reduced the SMS potential to a mean of 0.12 kg/kg with a 5th percentile of 0.1 kg/kg. This, they concluded, clearly showed that targets need to be established before subsystems become locked in to maximize mass reductions.
In the end, the analyses in this paper suggest that on average it may be possible to realize an entire additional kilogram removed (and almost certainly, in 95% of cases, 0.7 kg) for every kilogram removed through more novel methods. This is much larger than previously reported expert based-estimates which commonly center around 0.5 kg/kg. Those additional kilograms could transform the impact of investments in mass saving technologies. Consider that a SMS potential around 1 changes a 10% primary mass reduction...into a 20% reduction if load path and customer requirements remain unchanged. On average, that mass savings translates into a 10% savings in fuel economy.
If realized in the US fleet alone, a 10% reduction translates into savings of approximately 0.9 million barrels of petroleum per day (currently the US uses about 19 million barrels per day), or almost 200 million metric tons of carbon dioxide equivalent per year. Given the direct tie between mass and fuel use, challenging the industry to remove this additional mass is an important step toward a more sustainable automotive fleet.—Alonso et al.
Elisa Alonso, Theresa M. Lee, Catarina Bjelkengren, Richard Roth, and Randolph E. Kirchain (2012) Evaluating the Potential for Secondary Mass Savings in Vehicle Lightweighting. Environmental Science & Technology doi: 10.1021/es202938m